中国跨境进口电商企业的时空特征及影响因素分析

以中国361个地级行政区为空间单元，运用核密度、空间自相关、空间计量回归方法，研究中国跨境进口电商企业的时空特征及其影响因素。结果表明：①2004—2018年间中国跨境进口电商企业从“萌芽期”“发展期”到“平缓期”呈阶段性发展；企业分布涉及城市不断增加，从东部向中部逐步扩散，多中心化更加明显，大城市带动周边城市发展范围扩大。②跨境进口电商企业在全国范围内呈现“东多西少，南多北少”的分布特征，城市层面具有较强的集聚特点，形成“两大两小”不同分布模式的跨境进口电商企业集聚区。③跨境进口电商企业的空间分布是多因素共同作用的结果，集聚经济、交通运输水平、网络设施水平、物流发展水平对此影响较大。

Spatio-temporal characteristics and influencing factors of cross-border import e-commerce enterprises in China

Basing on the data of 361 prefecture-level units in China,this paper researched spatiotemporal characteristics and influencing factors of cross-border import e-commerce enterprises by using kernel density,spatial autocorrelation and spatial quantitative regression methods. The results were as follows:1) From 2004 to 2018, China's cross-border import e-commerce enterprises developed in stages, going through three stages from "infancy", "development" to "stable".The cross-border import e-commerce enterprises distributed in an increasing number of cities, gradually spreading from the east to the middle, and polycentric was more obvious. The influence scope of large cities expanded, driving the development of surrounding cities.2) The cross-border import e-commerce enterprises presented the distribution characteristics of "more in the east and less in the west, more in the south and less in the north" nationwide. Enterprises presented obvious agglomerating characteristics at the urban level, forming "two big and two small" cross-border import e-commerce enterprise agglomeration area. Specifically, the large agglomeration area was the Pearl River delta area and the Yangtze River delta area, which showed the polycentric agglomeration pattern.The small agglomeration area was the Beijing-Tianjin-Hebei area and Chengdu-Chongqing area, which presented monocentric agglomeration pattern.3) The spatial distribution of cross-border import e-commerce enterprises was influenced by multiple factors. Agglomeration economy, transportation level and network facilities level had great influence on it, followed by the logistics development level and level of opening up, and then degree of policy support and economic development. Residents' education level had little influence.